Sex Differences in Epicardial Adipose Tissue: Association With Atrial Fibrillation Ablation Outcomes

Zhu, Jing; Zhuo, Kaimin; Zhang, Bo; Xie, Zhen; Li, Wenjia

doi:10.3389/fcvm.2022.905351

Cited by 3 publications

(1 citation statement)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The emergence of automatic segmentation models based on CT angiography and CACS scans has significantly advanced research on the relationship between EAT and cardiovascular adverse events, such as myocardial infarction ( 10 , 11 , 26 , 27 ). However, the investigation into the association between EAT and AF still lacks validation from large-scale cohorts ( 16 , 28 , 29 ). This discrepancy can be attributed to the limitations of existing EAT segmentation models when applied to scans from PCTV.…”

Section: Discussionmentioning

confidence: 99%

Automatic epicardial adipose tissue segmentation in pulmonary computed tomography venography using nnU-Net

Hu,

Jiang,

et al. 2023

Quant Imaging Med Surg

View full text Add to dashboard Cite

Background Epicardial adipose tissue (EAT) is a key aspect in the investigation of cardiac pathophysiology. We sought to develop a deep learning (DL) model for fully automatic extraction and quantification of EAT through pulmonary computed tomography venography (PCTV) images. Methods In this retrospective study, we included 128 patients with atrial fibrillation and PCTV from 2 hospitals. A DL model for automated EAT segmentation was developed from a training set of 51 patients and a validation set of 13 patients from hospital A. The algorithm was further validated using an internal test set of 16 patients from hospital A and an external test set of 48 patients from hospital B. The consistency and measurement agreement of EAT quantification were compared between the DL model and the conventional manual protocol using the Dice score coefficient (DSC), Hausdorff distance (HD95), Pearson correlation coefficient, and Bland-Altman plot. Results In the internal and external test set, automated segmentation with DL was successful in all cases. The total analysis time was shorter for DL than for manual reconstruction (5.43±2.52 vs. 106.20±15.90 min; P<0.001). The EAT segmented with the DL model had good consistency with manual segmentation (the DSC of the internal and external test sets were 0.92±0.02 and 0.88±0.03, respectively). The quantification of EAT evaluated with the 2 methods showed excellent correlation (all correlation coefficients >0.9; all P values <0.001) and minimal measurement difference. Conclusions The proposed DL model achieved fully automatic quantification of EAT from PCTV images. The yielded results were highly consistent with those of manual quantification.

show abstract

Section: Discussionmentioning

confidence: 99%

Automatic epicardial adipose tissue segmentation in pulmonary computed tomography venography using nnU-Net

Hu,

Jiang,

et al. 2023

Quant Imaging Med Surg

View full text Add to dashboard Cite

show abstract

Sex Differences in Atrial Fibrillation

Tamirisa¹,

Calvert²,

Dye³

et al. 2023

Curr Cardiol Rep

View full text Add to dashboard Cite

Characterization of Cardiac Fat in Atrial Fibrillation Patients Prior to Ablation Treatment

Peer-Zada,

Hamze,

Garcia

2023

Applied Sciences

View full text Add to dashboard Cite

Epicardial adipose tissue (EAT) and pericardial adipose tissue (PAT) contribute to the development of left atrial fibrillation (AF). The purpose of this study is to determine the factors influencing cardiac fat, evaluate its impact on heart function, and evaluate its role in the recurrence of AF. Cardiac MRI exams of n = 198 patients with paroxysmal AF were retrospectively analyzed to quantify EAT and PAT. Body mass index (BMI) showed significant associations with increased EAT, PAT, and total cardiac fat, particularly with the total end-systolic area (p < 0.001). Males were associated with increased PAT (r = −0.331, p < 0.001) and EAT (r = −0.168, p = 0.019). Increased PAT end-diastolic volume was also associated with an increase in LV mass (r = 0.249, p < 0.01). An inverse relationship between EAT end-systolic area and cardiac index (r = −0.220, p < 0.01) was observed. Although BMI did not significantly affect AF recurrence, overweight patients (36%) experienced slightly more AF recurrence than obese patients (33%). Obesity is substantially associated with an increase in EAT and PAT, while sex appears to play a greater role in PAT than EAT and decreased cardiac function.

show abstract

Sex Differences in Epicardial Adipose Tissue: Association With Atrial Fibrillation Ablation Outcomes

Cited by 3 publications

References 52 publications

Automatic epicardial adipose tissue segmentation in pulmonary computed tomography venography using nnU-Net

Automatic epicardial adipose tissue segmentation in pulmonary computed tomography venography using nnU-Net

Sex Differences in Atrial Fibrillation

Characterization of Cardiac Fat in Atrial Fibrillation Patients Prior to Ablation Treatment

Contact Info

Product

Resources

About